interventionMatrix | R Documentation |
Calculate interventional distributions from a probability table or matrix of multivariate probability distributions.
interventionMatrix(x, variables, condition, dim = NULL, incols = FALSE) interventionTable(x, variables, condition)
x |
An array of probabilities. |
variables |
The margin for the intervention. |
condition |
The dimensions to be conditioned upon. |
dim |
Integer vector containing dimensions of variables. Assumed all binary if not specified. |
incols |
Logical specifying whether not the distributions are stored as the columns in the matrix; assumed to be rows by default. |
This just divides the joint distribution p(x) by p(v | c), where
v is variables
and c is condition
.
Under certain causal assumptions this is the interventional distribution p(x \,|\, do(v)) (i.e. if the direct causes of v are precisely c.)
intervention.table()
is identical to interventionTable()
.
A numerical array of the same dimension as x.
interventionMatrix
: Interventions in matrix of distributions
Robin Evans
Pearl, J., Causality, 2nd Edition. Cambridge University Press, 2009.
conditionTable
, marginTable
set.seed(413) # matrix of distributions p = rdirichlet(10, rep(1,16)) interventionMatrix(p, 3, 2) # take one in an array ap = array(p[1,], rep(2,4)) interventionTable(ap, 3, 2)
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